HBeeID: a molecular tool that identifies honey bee subspecies from different geographic populations.

BACKGROUND: Honey bees are the principal commercial pollinators. Along with other arthropods, they are increasingly under threat from anthropogenic factors such as the incursion of invasive honey bee subspecies, pathogens and parasites. Better tools are needed to identify bee subspecies. Genomic data for economic and ecologically important organisms is increasing, but in its basic form its practical application to address ecological problems is limited. RESULTS: We introduce HBeeID a means to identify honey bees. The tool utilizes a knowledge-based network and diagnostic SNPs identified by discriminant analysis of principle components and hierarchical agglomerative clustering. Tests of HBeeID showed that it identifies African, Americas-Africanized, Asian, and European honey bees with a high degree of certainty even when samples lack the full 272 SNPs of HBeeID. Its prediction capacity decreases with highly admixed samples. CONCLUSION: HBeeID is a high-resolution genomic, SNP based tool, that can be used to identify honey bees and screen species that are invasive. Its flexible design allows for future improvements via sample data additions from other localities.

Whole-genome resequencing of two elite sires for the detection of haplotypes under selection in dairy cattle.

Using a combination of whole-genome resequencing and high-density genotyping arrays, genome-wide haplotypes were reconstructed for two of the most important bulls in the history of the dairy cattle industry, Pawnee Farm Arlinda Chief ("Chief") and his son Walkway Chief Mark ("Mark"), each accounting for ∼7% of all current genomes. We aligned 20.5 Gbp (∼7.3× coverage) and 37.9 Gbp (∼13.5× coverage) of the Chief and Mark genomic sequences, respectively. More than 1.3 million high-quality SNPs were detected in Chief and Mark sequences. The genome-wide haplotypes inherited by Mark from Chief were reconstructed using ∼1 million informative SNPs. Comparison of a set of 15,826 SNPs that overlapped in the sequence-based and BovineSNP50 SNPs showed the accuracy of the sequence-based haplotype reconstruction to be as high as 97%. By using the BovineSNP50 genotypes, the frequencies of Chief alleles on his two haplotypes then were determined in 1,149 of his descendants, and the distribution was compared with the frequencies that would be expected assuming no selection. We identified 49 chromosomal segments in which Chief alleles showed strong evidence of selection. Candidate polymorphisms for traits that have been under selection in the dairy cattle population then were identified by referencing Chief's DNA sequence within these selected chromosome blocks. Eleven candidate genes were identified with functions related to milk-production, fertility, and disease-resistance traits. These data demonstrate that haplotype reconstruction of an ancestral proband by whole-genome resequencing in combination with high-density SNP genotyping of descendants can be used for rapid, genome-wide identification of the ancestor's alleles that have been subjected to artificial selection.

Diversity and strain specificity of plant cell wall degrading enzymes revealed by the draft genome of Ruminococcus flavefaciens FD-1.

BACKGROUND: Ruminococcus flavefaciens is a predominant cellulolytic rumen bacterium, which forms a multi-enzyme cellulosome complex that could play an integral role in the ability of this bacterium to degrade plant cell wall polysaccharides. Identifying the major enzyme types involved in plant cell wall degradation is essential for gaining a better understanding of the cellulolytic capabilities of this organism as well as highlighting potential enzymes for application in improvement of livestock nutrition and for conversion of cellulosic biomass to liquid fuels. METHODOLOGY/PRINCIPAL FINDINGS: The R. flavefaciens FD-1 genome was sequenced to 29x-coverage, based on pulsed-field gel electrophoresis estimates (4.4 Mb), and assembled into 119 contigs providing 4,576,399 bp of unique sequence. As much as 87.1% of the genome encodes ORFs, tRNA, rRNAs, or repeats. The GC content was calculated at 45%. A total of 4,339 ORFs was detected with an average gene length of 918 bp. The cellulosome model for R. flavefaciens was further refined by sequence analysis, with at least 225 dockerin-containing ORFs, including previously characterized cohesin-containing scaffoldin molecules. These dockerin-containing ORFs encode a variety of catalytic modules including glycoside hydrolases (GHs), polysaccharide lyases, and carbohydrate esterases. Additionally, 56 ORFs encode proteins that contain carbohydrate-binding modules (CBMs). Functional microarray analysis of the genome revealed that 56 of the cellulosome-associated ORFs were up-regulated, 14 were down-regulated, 135 were unaffected, when R. flavefaciens FD-1 was grown on cellulose versus cellobiose. Three multi-modular xylanases (ORF01222, ORF03896, and ORF01315) exhibited the highest levels of up-regulation. CONCLUSIONS/SIGNIFICANCE: The genomic evidence indicates that R. flavefaciens FD-1 has the largest known number of fiber-degrading enzymes likely to be arranged in a cellulosome architecture. Functional analysis of the genome has revealed that the growth substrate drives expression of enzymes predicted to be involved in carbohydrate metabolism as well as expression and assembly of key cellulosomal enzyme components.